We improve on the popular conformer architecture by replacing the depthwise temporal
convolutions with diagonal state space (DSS) models. DSS is a recently introduced variant …

Text input is a critical component of any general purpose computing system, yet efficient and
natural text input remains a challenge in AR and VR. Headset based hand-tracking has …

Neural network pruning compresses automatic speech recognition (ASR) models effectively.
However, in multilingual ASR, language-agnostic pruning may lead to severe performance …

There is growing interest in unifying the streaming and full-context automatic speech
recognition (ASR) networks into a single end-to-end ASR model to simplify the model …

We propose a novel deliberation-based approach to end-to-end (E2E) spoken language
understanding (SLU), where a streaming automatic speech recognition (ASR) model …

End-to-end (E2E) spoken language understanding (SLU) systems that generate a semantic
parse from speech have become more promising recently. This approach uses a single …

In this paper, we propose a joint federated learning (FL) and personalization method for on-
device ASR adaptation. Starting with a Conformer-based RNN-T as the ASR model …

Streaming Automatic Speech Recognition (ASR) has gained significant attention across
various application scenarios, including video conferencing, live sports events, and …

In this paper, we propose a Unified pre-training Framework for Online and Offline (UFO2)
Automatic Speech Recognition (ASR), which 1) simplifies the two separate training …

We show how factoring the RNN-T's output distribution can significantly reduce the
computation cost and power consumption for on-device ASR inference with no loss in …